code: def __init__(
      self, inplanes, planes, stride=1, downsample=None, gcb_config=None
  ):
      super(BasicBlock, self).__init__()
      self.conv1 = nn.Conv2D(
          inplanes,
          planes,
          kernel_size=3,
          stride=stride,
          padding=1,
          bias_attr=False,
      )
      self.bn1 = nn.BatchNorm2D(planes, momentum=0.9)
      self.relu = nn.ReLU()
      self.conv2 = nn.Conv2D(
          planes,
          planes,
          kernel_size=3,
          stride=1,
          padding=1,
          bias_attr=False,
      )
      self.bn2 = nn.BatchNorm2D(planes, momentum=0.9)
      self.downsample = downsample
      self.stride = stride
      self.gcb_config = gcb_config
  
      if self.gcb_config is not None:
          gcb_ratio = gcb_config["ratio"]
          gcb_headers = gcb_config["headers"]
          att_scale = gcb_config["att_scale"]
          fusion_type = gcb_config["fusion_type"]
          self.context_block = MultiAspectGCAttention(
              inplanes=planes,
              ratio=gcb_ratio,
              headers=gcb_headers,
              att_scale=att_scale,
              fusion_type=fusion_type,
          )
  
file_path: PaddleOCR/ppocr/modeling/backbones/table_master_resnet.py
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
label_desc: Use image node_id 1 to create a new BasicBlock object from inherited base classes: nn with example: obj = BasicBlock(inplanes, planes, stride, downsample, gcb_config)